Short-Term Power Prediction of a Photovoltaic Power Station Based on the SSA-CEEMDAN-FCN Model

Photovoltaic power generation is greatly affected by weather factors. To improve the prediction accuracy of photovoltaic power generation, complete ensemble empirical mode decomposition with an adaptive noise algorithm (CEEMDAN) is proposed to preprocess the power sequence. Then, the full convolutio...

Descripción completa

Detalles Bibliográficos
Autores principales: Qu, Zhaoyang, Qin, Shaohua, Xiong, Genxin, Zhu, Xinpo, Ling, Fan, Wang, Yukun, Kong, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522494/
https://www.ncbi.nlm.nih.gov/pubmed/36188685
http://dx.doi.org/10.1155/2022/6486876

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522494/
https://www.ncbi.nlm.nih.gov/pubmed/36188685
http://dx.doi.org/10.1155/2022/6486876

Ejemplares similares